Question 1

Scenario: You are managing an application on Google Cloud Platform (GCP) that serves a global audience with both static and dynamic content. To improve user experience, you implemented a caching layer in Cloud Memorystore (Redis). However, as usage has increased, so has the cost of maintaining the Redis cache. You notice that the Redis cache hit rate is lower than expected, with many requests still reaching the backend, which drives up costs for both the cache and backend resources.What action would be the most effective way to optimize cache utilization and reduce costs?

Options :

A : Review and update cache keys to ensure that frequently requested data is cached effectively.

B : Increase the Redis instance size to improve cache performance and hit rates.

C : Implement a load balancer with round-robin routing to distribute requests evenly across instances.

D : Set a lower time-to-live (TTL) for cached items to keep the cache fresher.

Answer: A

Question 2

A FinOps team is building a custom integration to aggregate and analyze cloud spend from AWS, Azure, and GCP. They aim to create a unified dashboard for real-time cost insights across all cloud environments. The team needs to decide on the appropriate tools and configurations for data retrieval and aggregation to support both historical and real-time analysis. Which two of the following approaches should they take to ensure reliable, scalable cost data ingestion and analysis?

Options :

A : Set up AWS Lambda functions to retrieve cost data from AWS Cost Explorer API and store it in Amazon RDS for continuous historical and real-time analysis.

B : In GCP, configure the Billing Export to BigQuery for detailed cost information, then build custom SQL queries to extract real-time cost trends and export these summaries to a centralized reporting platform.

C : Leverage Amazon Athena with the AWS Cost and Usage Report (CUR) to perform SQL-based analysis on AWS costs directly, using Athena to feed this data into a centralized dashboard for cross-cloud cost analysis.

D : Use Azure Data Factory (ADF) to schedule and automate the ingestion of data from Azure Cost Management API, storing the data in a centralized data lake such as Azure Data Lake or AWS S3.

Answer: B,D

Question 3

Your organization uses Kubecost to manage Kubernetes costs and has recently noticed a rise in idle resources across various clusters. The FinOps team needs to reduce costs by optimizing these idle resources. Which of the following actions would be most effective using Kubecost? (Select two correct answers)

Options :

A : Implement Kubecost’s node right-sizing recommendations to allocate optimal instance types based on usage patterns.

B : Disable Kubecost’s cost allocation feature to focus only on cluster-wide cost reductions.

C : Set higher resource requests for applications to maximize node utilization.

D : Leverage Kubecost’s idle resource tracking to identify and consolidate underutilized nodes.

E : Use Kubecost’s showback functionality to distribute idle costs among teams proportionally.

Answer: A,D

Question 4

An enterprise cloud customer received a custom rebate on cloud spend for the last quarter due to exceeding their usage commitment. The cloud provider’s rebate terms state that the rebate will only apply to actual consumption that meets specific cost-saving initiatives, such as using Reserved Instances and reducing idle resources. The FinOps team wants to ensure they maximize these rebate opportunities while keeping spend efficient across the next quarter. What is the most effective strategy to achieve this?

Options :

A : Encourage teams to maximize their consumption without focusing on specific instance types to guarantee high usage meets rebate requirements.

B : Consolidate workloads onto fewer, higher-cost instances to increase spend quickly, ensuring rebate criteria are met.

C : Increase reliance on pay-as-you-go instances to ensure flexibility and focus on high usage to earn future rebates.

D : Implement strict policies requiring all teams to use Reserved Instances for predictable workloads and run periodic audits for idle resources.

Answer: D

Question 5

A large organization is setting up a FinOps governance framework to manage cloud costs across multiple departments. They want to ensure each department has visibility into its spending and accountability for optimizing it. Which of the following approaches best aligns with the principles of FinOps governance in a large-scale environment?

Options :

A : Enforce a fixed-budget model across all departments, requiring approval from the CFO for any cloud spending changes.

B : Centralize all cloud cost management in a single FinOps team that allocates budgets based solely on past departmental expenditures.

C : Implement a decentralized model where each department independently manages and reports on its cloud costs without oversight from a central FinOps team.

D : Set up a FinOps Center of Excellence (CoE) that provides standardized cost management tools and practices, while enabling departments to monitor and optimize their own cloud spending.

Answer: D

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